Model ML says it signed as many contracts in the last seven days as in all of Q4, which Chaz Englander cites as proof AI products deliver tangible value.
Model ML's agentic workspace connects analysts' files, email, CRM and data vendors, and turns earnings summaries into slides that are 90 to 95 percent finished.
Chaz Englander argues 2025 was the year the industry moved from testing AI to using it, and that AI is now the top item on senior executives' agendas at banks and private equity firms.
Model ML Gives Wall Street Analysts an Agentic Workspace
Model ML is betting that financial firms are finally ready to buy agentic AI, and that analyst work is where it pays off first. Its workspace connects to a firm's own data, so routine outputs like earnings summaries arrive nearly finished. Buyers have moved from experiments to purchases as models match or beat humans at extracting data, and contract volume has jumped as a result.
Takeaways
Model ML is an agentic workspace for finance. It offers Office-style spreadsheets, slides and documents on an agentic system that mirrors a human's access to files, email, CRM, data vendors and public filings. Analysts get a spreadsheet already connected to their data.
Analyst work became the focus after an experiment. The brothers built an agent that wrote investment one-pagers, but about 90% of the content had no link to the triggering email. That pushed them to automate analyst tasks like earnings summaries, which take days by hand and which Model ML gets 90 to 95 percent finished.
Financial firms moved from testing AI to buying. Chaz says 2025 is when the industry shifted from proof of concepts to real use, and AI now tops senior executive agendas. Model ML signed as many contracts in seven days as in all of Q4.
Models now beat humans at data extraction. Chaz argues models are already more accurate than people at turning filings into structured data, though confidence will take time. Arnie points to vision models combined with OCR as the turning point for reading tables and charts.
Large institutions already use the product. About 10% of the largest private equity firms and investment banks use Model ML, along with asset managers, sovereign wealth funds and venture firms. About 80% of customers are in the US, and buying needs sponsorship from the top and from implementers.
Clear roles and honesty hold the founding team together. Arnie runs engineering while Chaz handles finance, commercials and products. Arnie says co-founders need transparency because most startup failures come from falling out, and says hiring interviews should test how much the team will enjoy working with a candidate.
Advice for founders
Arnie says starting a company suits the passionate, but it is very hard and may take five to fifteen years.
Chaz says the worst case of founding a company is learning a lot in a short time, since jobs will still be there.
Chaz says people should unlearn what they picked up in five years at large companies.
Chaz says founders should move to San Francisco or another tier one city, because many global technology decision makers sit there.
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On this episode 3
Show 1
Michael Seibel pushed the brothers in 2017 to report numbers weekly or daily rather than monthly.